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7a80908c2b2e6b54f11a2737668f11a49e1df469 | f3843622adeae8d70b9ea87047379ebedf0a0193 | /R/kmr_histogram.R | 65347e7270935d92c68f66492b68eafc72a77c0f | [] | no_license | c5sire/kmerize | 0dda2ed25444d8c54c6b09459f81dd6a5c971bfb | 0f6aa30504faa3c2cdd9ac3bf5dde64d2297af53 | refs/heads/master | 2021-01-14T17:17:21.430902 | 2020-06-03T14:29:38 | 2020-06-03T14:29:38 | 242,692,612 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 504 | r | kmr_histogram.R | #' kmr_histogram
#'
#' @param db path to kmc3 database
#' @param out filename for histogram data
#'
#' @return
#' @export
#'
# @examples
kmr_histogram <- function(db, out = paste0("hist_", basename(db), ".txt")) {
if (!dir.exists(dirname(out))) dir.create(dirname(out))
bn <- basename(db)
db <- file.path(db, bn)
... |
53e680b67eea3f64078152cc544b4715913e7035 | ea805d721a3cdc2db7a75e38a9b212e4e1885778 | /ribiosArg/man/parseStrings.Rd | 3feb80bc728bd354f6bbad5d2aa3e209194ee465 | [] | no_license | grst/ribios | 28c02c1f89180f79f71f21a00ba8ad8c22be3251 | 430056c85f3365e1bcb5e565153a68489c1dc7b3 | refs/heads/master | 2023-06-01T04:48:20.792749 | 2017-04-10T14:28:23 | 2017-04-10T14:28:23 | 68,606,477 | 0 | 0 | null | 2016-09-19T13:04:00 | 2016-09-19T13:04:00 | null | UTF-8 | R | false | false | 1,228 | rd | parseStrings.Rd | \name{parseStrings}
\alias{parseStrings}
\title{Parse collapsed multiple options into a vector of character strings}
\description{
This function parses collapsed multiple options into a vector of
character strings. Each option is optionally trimmed of leading and tailing empty
spaces given by \code{trim}. See exa... |
4471545ebd73c11d8d4746464f4c06b88d8f6aad | ff25dc05d9be0f35bf3be844116c130197d93ef1 | /man/alpha.aci.Rd | a3e0452962d1bcdfa37c508eee67b06176d59c5d | [] | no_license | Justin8428/multicon | a7389643ea7b3fa36b3d3197c2eb16d34dd2644f | d01cc51f116e165aabd181ac1df355db35e57b4c | refs/heads/master | 2023-03-16T12:50:33.453390 | 2015-01-28T00:00:00 | 2015-01-28T00:00:00 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,822 | rd | alpha.aci.Rd | \name{alpha.aci}
\alias{alpha.aci}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{
Alpha Confidence Interval
}
\description{
Computes the asymptotic confidence interval for Cronbach's alpha following the method outlined by Koning & Franses (2003). }
\usage{
alpha.aci(x, k, n, CI = 0.95)
}
%- may... |
8c5331a2afa187b9367c56486861b115cb6a9363 | 17afbc057e8fba98bb687d12a3fe3dd017e99e86 | /man/HEQueryCountWorker.Rd | ca973ddb866a6a4c73a3eeae4c31f23c5e4771e6 | [] | no_license | cran/distcomp | 4fcb588c4210c0cd1309055a5946181d479b1d22 | f87e29d541054abb52404f194f2cfe6358babb76 | refs/heads/master | 2022-09-17T21:48:41.342751 | 2022-09-01T20:00:02 | 2022-09-01T20:00:02 | 36,823,221 | 0 | 1 | null | null | null | null | UTF-8 | R | false | true | 4,875 | rd | HEQueryCountWorker.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/querycount.R
\name{HEQueryCountWorker}
\alias{HEQueryCountWorker}
\title{Create a homomorphic computation query count worker object for use with master objects generated by \code{\link[=HEQueryCountMaster]{HEQueryCountMaster()}}}
\description... |
ec657ceb12a61e0f6309775f0611286cb891a560 | 587285694e7c0dab9acb9fab2f457726f4583bb1 | /R/extr_leafArea_fct.r | 47eae6b7b6c4fd04885dc693a7f74afcea6038f8 | [] | no_license | hjkluo/RapidACi0927 | 76f4c3628d5aad35466b1104deb8e9d02995c41e | 7f9ea9790169f828183ebd021d0f8f57ab65ccc2 | refs/heads/master | 2022-12-22T07:20:14.409532 | 2020-07-20T13:28:52 | 2020-08-08T14:13:43 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 569 | r | extr_leafArea_fct.r | #' extr_leafArea function
#'
#' @description Hidden function. Retrieves a dataframe of leaf surface area by sample from
#' WinSEEDLE software output files
#'
#' @param WinSEEDLE_filepath path for a winSEEDLE file (from the working directory)
#'
#' @return A dataframe of sample_ID with date and leaf area
extr_leafAre... |
1c3744d667c8140890d2ff138b752ffb19edad07 | 3031e443423a08fe9e33e369fb0e92fc8f67816a | /man/graphs3.Rd | b130331692765ba3e2d37074d53652d879532c09 | [] | no_license | HRDAG/DGA | e441b0e3638d536be245bcb6af87c45638760cf7 | c3a684dca92dc42977969c9d80b69eadb7e7f579 | refs/heads/master | 2021-07-08T06:27:23.494429 | 2021-05-04T20:21:02 | 2021-05-04T20:21:02 | 20,732,790 | 2 | 2 | null | 2021-05-04T20:01:33 | 2014-06-11T16:40:09 | R | UTF-8 | R | false | true | 597 | rd | graphs3.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data.R
\docType{data}
\name{graphs3}
\alias{graphs3}
\title{All Decomposable Graphical Models on Three Lists}
\format{
A list of lists. graphs3[[i]] is the \code{i}th model under
consideration. This consists of graphs3[[i]]$C, all of the cliq... |
a4dc09b2534bf9abb33caaca1483569735088ac9 | cac8e9de4fb2fba4caa7a626bd58c82abf118fd5 | /R_code_concepts_Illustration/R_sq_adj_R_saga.R | 59ac79579bd4a8d5546a0a9a64138a2187f7f52a | [] | no_license | rheasukthanker/Computational_Statistics_ETH | 63ed3b680573223bd52691b526e93b571b97d272 | ad29f3cd2f3744386da361c44e8eec4357f597b3 | refs/heads/main | 2023-06-26T16:03:29.502249 | 2021-07-31T06:33:51 | 2021-07-31T06:33:51 | 391,268,900 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 531 | r | R_sq_adj_R_saga.R | #RSS R squared and adjusted R squared
#R^2 vs Adjusted R squared
?rnorm
n=500
R_sq=rep(0,n-3)
Adj_Rsq=rep(0,n-3)
for (i in c(2:498))
{
X=rnorm(n*i)
X=matrix(X,nrow=n,ncol=i)
X
y=2*X[,1]+4*X[,2]+rnorm(n)
fit_diffnp<-lm(y~X)
R_sq[i-1]=summary(fit_diffnp)$r.squared
Adj_Rsq[i-1]=summary(fit_diffnp)$adj.r.squared
}
par(mfro... |
2aa2647f7378d8c3c8938a1c5c3a81788dfbd45b | 216b7cbdcd61f0cdfc5a8f74e8a24d68b56c3057 | /R_scripts/007_gca_property_xfer.R | 838180090c5f7c1a586e332d00d070c249096161 | [] | no_license | Preetis17/CapstoneProject | 7e0ebb9e02958ea100cc8153e625b4fe27644997 | c026bc5369b77d9d46ffffb2f5f7c629d62ea4ad | refs/heads/master | 2020-03-23T01:08:46.791202 | 2018-12-13T01:26:08 | 2018-12-13T01:26:08 | 140,902,835 | 0 | 2 | null | 2018-12-12T04:50:34 | 2018-07-14T00:07:43 | Jupyter Notebook | UTF-8 | R | false | false | 11,819 | r | 007_gca_property_xfer.R |
# ... -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
# ... file : grid_cell_assignment.R
# ...
# ... organizer to prep data sets for submit to which_grdi_cell_function()
# ...
# ... ref : https://stackoverflow.com/questions/21977720/
# ... r-finding-closest-neighboring-point-... |
4966101834815d41caa84f44aad663215454c6cc | 712f63922a9477ce44541aa97fb26e75a77e2420 | /man/plot.FCVAR_grid.Rd | 94537fd3a26a7c443abc179ad1c2dbdb72123fc7 | [] | no_license | LeeMorinUCF/FCVAR | caacba62754044a5ff318144ac97d2c10e31521f | 3a7684ade7d27dbaad0907229c11ed8ed8d8ad85 | refs/heads/master | 2022-06-04T08:09:57.346547 | 2022-05-04T18:54:02 | 2022-05-04T18:54:02 | 217,621,323 | 3 | 2 | null | null | null | null | UTF-8 | R | false | true | 2,273 | rd | plot.FCVAR_grid.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/FCVAR_aux.R
\name{plot.FCVAR_grid}
\alias{plot.FCVAR_grid}
\title{Plot the Likelihood Function for the FCVAR Model}
\usage{
\method{plot}{FCVAR_grid}(x, y = NULL, ...)
}
\arguments{
\item{x}{An S3 object of type \code{FCVAR_grid} output from ... |
cc0b2a6d449f5ca326aafcdd946daaa0291c3989 | c2728bfe5bf2230eca3b3c7069b78c97b2a2c6bc | /proyecto_clustering/script_clustering.R | e9f93180f25d17f75d39e08c6e54e0c760b63751 | [] | no_license | pedrohserrano/topological-data-analysis | 4d1a37269d7b2458c4cfe52b00d67989b28892ac | 049346a32708a87814c24e1de002254095eeb709 | refs/heads/master | 2021-06-18T12:19:06.153829 | 2017-06-17T03:45:35 | 2017-06-17T03:45:35 | 55,701,407 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 10,225 | r | script_clustering.R | #CLUSTERING
#----------------------------- LIBRARIES -----------------------------
#install.packages("fpc")
#install.packages("kernlab")
#install.packages("dbscan")
#install.packages("jsonlite")
#install.pachkages("qrage")
library(fpc)
library(dbscan)
library(kernlab)
library(jsonlite)
library(igraph)
library(RColorBr... |
d2da2544d822e9b8fb94673fb6fb58ac9c766149 | 2f5ed17ace2ae9c7a1102617ca1dcc91ae1f2466 | /man/qqnormsim.Rd | 7c7c1fa80afd225f2df06a1fe6fab04e4966d117 | [] | no_license | jbryer/DATA606 | 0b9f79590d257040e997b48a78c3b0c9ce0b006c | 3c702d4b08af2e2258d54dc31b13ae61a8e29bcd | refs/heads/master | 2023-08-17T04:27:03.710532 | 2023-08-11T14:59:38 | 2023-08-11T14:59:38 | 39,025,976 | 6 | 15 | null | 2022-11-11T22:27:03 | 2015-07-13T17:09:52 | HTML | UTF-8 | R | false | true | 275 | rd | qqnormsim.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/qqnormsim.R
\name{qqnormsim}
\alias{qqnormsim}
\title{Simulates QQ-plots with the given data.}
\usage{
qqnormsim(dat)
}
\description{
Simulates QQ-plots with the given data.
}
\author{
OpenIntro
}
|
80b9475072c205f98fbbab396008a783256ea2db | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/PROscorer/examples/fsfi.Rd.R | f4e69b69ba1d7a0cff487367eae9143fa2db2920 | [] | no_license | surayaaramli/typeRrh | d257ac8905c49123f4ccd4e377ee3dfc84d1636c | 66e6996f31961bc8b9aafe1a6a6098327b66bf71 | refs/heads/master | 2023-05-05T04:05:31.617869 | 2019-04-25T22:10:06 | 2019-04-25T22:10:06 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 490 | r | fsfi.Rd.R | library(PROscorer)
### Name: fsfi
### Title: Score the Female Sexual Function Index (FSFI)
### Aliases: fsfi
### ** Examples
# Creating data frame of fake FSFI responses
dat <- PROscorerTools::makeFakeData(n = 10, nitems = 19, values = 0:5,
prefix = 'f')
dat1 <- PROscorerTools::m... |
a6d4cdfcba65d62b62bd1f0721b25e10d6ae65b8 | c194c5236006a758b29bd4d530ad563dc9ecab7e | /inst/apps/diagram_both/server.R | 8d522c4c9f0a068823d91b5857f1b910dc1e8a62 | [] | no_license | Auburngrads/teachingApps | 1087c20a21992433a2f8451db7b1eaa7d1d2cb89 | b79c192e5f74c5e8376674d4fb9e0b95a426fe03 | refs/heads/master | 2021-03-16T07:49:56.579527 | 2020-06-14T12:10:12 | 2020-06-14T12:10:12 | 51,677,745 | 15 | 7 | null | 2018-03-01T03:44:58 | 2016-02-14T03:22:47 | R | UTF-8 | R | false | false | 204 | r | server.R | server = function(input, output, session) {
output$plotreal <- renderPlot({
par(oma = c(0,0,0,0), mar = c(4,4,2,2))
input$evalreal
return(isolate(eval(parse(text=input$realplot))))
})
} |
ee5f0cd526a79dcf3256b5e52d9e2df2a35858a6 | 3976972fec0a7e5002b741e9d7d55ee522370f13 | /ctseq/rFunctions.R | aa8f4d871e2c2077caebebdefc2d3e714c3bb837 | [
"MIT"
] | permissive | jzfarmer/KailosProject | 92a7581ca96930b5b6573bb32574e8fda35d0208 | 42d70d6470955ea47ee40aed2d66bd9981f1cfef | refs/heads/main | 2023-06-23T21:55:42.840363 | 2021-07-27T18:55:22 | 2021-07-27T18:55:22 | 374,232,234 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 10,368 | r | rFunctions.R | # make sure a list of names is in the correct format
# taking in a list of names. if the name starts with a number, it adds an X to the beginning.
# adds an X to the beginning because R will add X's to names beginning with integers
# returns back the modified names.
formatNames=function(listOfNames){
newListOfNames=c... |
7f18b56c4284e8edcaeec404f3e4abb0a3b0f5c3 | 25ea70b6f8151a5994edf7afc9c65653eaf1cbc2 | /day1.R | e5b993eeecb28fc371abb4836a4bde84bad284c0 | [] | no_license | yoooongd/test2 | 4c665d8033c8d6f821668ced4b14cd958ffc7932 | 6a36c1da161315b863876fdecd6b876bf6028cad | refs/heads/master | 2020-04-22T14:39:49.946131 | 2019-02-13T12:26:49 | 2019-02-13T12:26:49 | 170,451,352 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 205 | r | day1.R | xNum <- c(1, 3, 5, 7)
xLog <- c(TRUE, T, F, T)
xChar <- c("a","b","c","d")
df <-data.frame(xNum, xLog, xChar)
df
str(df)
df$Name <- c("Kim","Park","Tom","Joe")
df
df<- transform(df, Age=c(10,20,30,40))
df
|
81f06071cbd25a4955353165d0b526201e006b87 | 9ea744d0e28fe4fc4d3e1e00f7ec53ea054b8cd0 | /R/nextstrain.json.R | c6acba9d0ed589fcfbdcc2cab53bcd9bc6b9bc4f | [] | no_license | YuLab-SMU/treeio | 8d434454f25336859e0e0c12fc65029a310b638b | c3f7b8e6df5f768f53e33b46b3e13dd529bb4f56 | refs/heads/devel | 2023-09-01T19:44:13.166325 | 2023-08-25T04:27:18 | 2023-08-25T04:27:18 | 75,700,092 | 56 | 17 | null | 2023-08-25T04:25:14 | 2016-12-06T06:05:56 | R | UTF-8 | R | false | false | 2,760 | r | nextstrain.json.R | #' @title read.nextstrain.json
#' @param x the json tree file of auspice from nextstrain.
#' @return treedata object
#' @export
#' @author Shuangbin Xu
#' @examples
#' file1 <- system.file("extdata/nextstrain.json", "minimal_v2.json", package="treeio")
#' tr <- read.nextstrain.json(file1)
#' tr
read.nextstrain.json <-... |
4f01d34671d95156c2d77927244dbf60bb297f8a | 9570c514cd5e90c04c3cf902c4a3e120afa97069 | /Paper_plots/fig3_all_model_intersects_per_pop_plus_tables4_5.R | b6b6693add974b70576b606c76a71de9b669665f | [] | no_license | WheelerLab/ML-PredictDB | 983ce8652bff0818ad35e7cd29d662012e611c3e | 8110036ec7b746aab977e38b7fcc1ce8bd63adda | refs/heads/master | 2021-03-09T17:09:59.212863 | 2020-11-30T02:45:01 | 2020-11-30T02:45:01 | 246,360,407 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 8,340 | r | fig3_all_model_intersects_per_pop_plus_tables4_5.R | #Make another Figure 3 Boxplot. Where the gene intersects per MESA training subpopulation is used per algorithm.
#e.g In AFA, all gene intersects of EN, RF, SVR, KNN
library(data.table)
library(dplyr)
library(tidyverse)
library(ggplot2)
"%&%" = function(a,b) paste (a,b,sep="")
#df <- NULL
algs <- c("en", "knn", "rf"... |
00c4cf7919a7ab7a9306181f7ed4484cdb8b8cc2 | a30c029a2e6dc3a621b20712d32b1233afc0eb02 | /connection/RMySQL.R | eb16a47b57212ea25bf85f48f4ca8842e5e0dced | [] | no_license | floss-for-fun/r-for-fun | 141af0c89a35daedbc82e22f1fa7134ac1549658 | 011862312c66b47e6ce49c1ba38159e4e9df01ef | refs/heads/master | 2020-04-13T21:14:03.459744 | 2017-07-05T01:29:24 | 2017-07-05T01:29:24 | 20,584,410 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 500 | r | RMySQL.R | # load library
library(RMySQL)
# connect to database 'test' in localhost, username 'root',
# with no password
mydb <- dbConnect(MySQL(), user='root', password='',
dbname='test', host='localhost')
# show all tables in database
dbListTables(mydb)
# show all column in table
dbListFields(mydb, 'nama_table')
# g... |
48e1373c26248561e351c0b3b1cc7fa54130a3da | db23803c56eb7f0f7e0239ba45ef5aa5f1e26fc6 | /scripts/figure_scripts/Supp_EC_spearman_w_NSTI_and_scrambled.R | 0589f5dc034e6c6c1f436c68b81bd14ef270d70c | [] | no_license | weibokong27/picrust2_manuscript | ed362146df5f917e3f92aa012ba5a864dc2928fa | dd4e2daa0b7058fa0ef46bc8f02c052f226c34ed | refs/heads/master | 2022-07-02T14:47:02.757223 | 2020-05-16T12:42:29 | 2020-05-16T12:42:29 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,485 | r | Supp_EC_spearman_w_NSTI_and_scrambled.R | ### Code to make figure contrasting EC correlations on each 16S validation dataset.
### Include all NSTI cut-offs in these plots.
rm(list=ls(all.names=TRUE))
library(ggplot2)
library(reshape2)
library(ggpubr)
library(cowplot)
library(ggbeeswarm)
setwd("/home/gavin/gavin_backup/projects/picrust2_manuscript/data/saved... |
68cb869aa00d9c1e37e213bc62d13414a94d05bc | a8ace6bed475a0017e4ecc91c4cfc6e42477892b | /man/get.best.templates.Rd | b403dbe5721e2f8ee2b615475906b38834c6d6a3 | [] | no_license | adbelazim/carSignal | 34993c617c92519eb35aa5a7d02e9202e879bb90 | 935e6fbd6c8d25ca514e1ed118f16342197116e3 | refs/heads/master | 2021-03-22T00:33:09.748942 | 2016-10-02T03:19:52 | 2016-10-02T03:19:52 | 69,776,080 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 1,260 | rd | get.best.templates.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/carSignal-v15.9.10.R
\name{get.best.templates}
\alias{get.best.templates}
\title{Busca la curva que mejor se ajuste a los templates entregados como entrada, con el propósito de calcular
el índice ARI.}
\usage{
get.best.templates(time.instants... |
d8f52b69c39dacf1fdb7cc7e8690e864f03a111f | 024b07663d349d5f2c6fd04db563307754a61ca4 | /SimulationChooseIVs/test/test_ChooseInstruments.R | a1a2144d91a348f66477e80dda8b43c6f34115a0 | [] | no_license | fditraglia/fmsc | b794059959705b68ea3ec992b48b8c0bf2affc73 | 5c913e7912a05064bc0d093ca7037bc6e32e8aae | refs/heads/master | 2021-06-30T14:32:59.409420 | 2016-09-02T15:30:06 | 2016-09-02T15:30:06 | 14,152,577 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,380 | r | test_ChooseInstruments.R | setwd("~/fmsc/ChooseInstruments")
library(Rcpp)
library(RcppArmadillo)
sourceCpp("simulation_functions_ChooseInstruments.cpp")
library(sem)
simple_dgp <- function(){
n <- 100
a0 <- 0.5
a1 <- 1
a2 <- 1
b0 <- 0.75
b1 <- 1.5
z0 <- rep(1, n)
z1 <- rnorm(n)
z2 <- rnorm(n)
x1 <- a0 + a1 * z1 + a2 * z... |
a56e306b2fe4bfdf34ee36cd1612548dc3eeea6d | 10d6629bf46a82c0f87bea8456d36e7b0e66df82 | /plot2.R | 514e3c9b8f2f3a4051d422ef89a62346c4349ac9 | [] | no_license | cosetta-lodovici/ExData_Plotting1 | e563c5c86bd7aba7210b7786ebc5d7a9180157fd | e5ecd6b0fc67922e8cf70b11413f64c73d8c0933 | refs/heads/master | 2021-01-21T18:10:47.502177 | 2017-05-22T12:48:52 | 2017-05-22T12:48:52 | 92,021,000 | 0 | 0 | null | 2017-05-22T06:52:14 | 2017-05-22T06:52:13 | null | UTF-8 | R | false | false | 460 | r | plot2.R | library (sqldf)
Sys.setlocale("LC_ALL", "English")
# read data
sourcefile <- "../household_power_consumption.txt"
DF <- read.csv.sql(sourcefile,sep=";",sql="select * from file where Date in ('1/2/2007','2/2/2007')")
# png file
png(file="plot2.png", width = 480, height = 480)
plot(as.POSIXct(paste(DF$Date,DF$Time),f... |
0ed47ce6a6305d7f9db7f04de900093bbf438c4c | af681784e683a9ff5b0e9b773504a934cc73cd7b | /Lab2_keane.R | 10a69a94ad81765ad09d586dc64ccf68a43cc062 | [] | no_license | jakeane/qss17_assignments | 0cf9850f07b0b538af801c416fbd24c54f8cdde4 | 778b6386a497be7281eed2c5c03d19b916cc26f4 | refs/heads/master | 2023-01-21T23:29:42.776236 | 2020-12-04T19:40:01 | 2020-12-04T19:40:01 | 295,878,104 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,318 | r | Lab2_keane.R | ## QSS 17
## John Keane
# Set up environment
library(tidyverse)
library(USAboundaries)
library(USAboundariesData)
library(gganimate)
library(sf)
library(transformr)
library(lubridate)
covid <- read_csv("https://raw.githubusercontent.com/nytimes/covid-19-data/master/us-counties.csv")
county_pop <- read_csv("projectData... |
26a2059c23c76cb6044790c617b0c3e81481fea1 | 07f2ed7b3565c8d6679da4084bbb39930221da20 | /src/R/HSROC/man/HSROC.Rd | 0890738fe77d482286625f903a4144ebc98ebcfb | [] | no_license | bwallace/OpenMeta-analyst- | 0fbc19f77018a72ce293e1c72e9b2c0a7eb3b615 | e3147cab25e773251e7052f3bf27852ea41d522e | refs/heads/master | 2021-01-21T04:37:15.296676 | 2020-07-28T00:52:29 | 2020-07-28T00:52:29 | 293,390 | 26 | 13 | null | 2020-07-28T00:52:30 | 2009-08-31T16:25:12 | Python | UTF-8 | R | false | false | 13,289 | rd | HSROC.Rd | \name{HSROC}
\alias{HSROC}
\title{A function for joint meta-analysis of sensitivity and specificity of a diagnostic test.}
\description{ This function is used to estimate the parameters of a hierarchical summary receiver operating characteristic (HSROC) model allowing for the reference standard to be possibly im... |
72977d25a4cd1ab10f336a376869e94d705de4b7 | 2ae4d59d4dfb7d0cd96f729aa03dba089f1fe024 | /titanic_analysis.R | f815bdd9dc18535da18179ded8434baaea5bf75d | [] | no_license | data-better/statistics | 7f854fc702611238a08db95fb4a124da521ea30a | 154ef9f62d8fcf4a2221db501ba01a496200a0a6 | refs/heads/main | 2023-05-31T08:18:13.406203 | 2023-05-10T06:45:29 | 2023-05-10T06:45:29 | 356,442,068 | 3 | 2 | null | null | null | null | UTF-8 | R | false | false | 2,157 | r | titanic_analysis.R | # 필요한 패키지 불러오기
library(shiny)
library(ggplot2)
library(dplyr)
# 타이타닉 데이터 불러오기
titanic <- read.csv("https://raw.githubusercontent.com/datasciencedojo/datasets/master/titanic.csv")
# R shiny 앱 만들기
ui <- fluidPage(
# 제목
titlePanel("타이타닉 데이터 분석"),
# 사이드바
sidebarLayout(
# 사이드바 패널
sidebarPane... |
8902f0030ddf165f77382226079615fed586e021 | b1d2dba7dac3185e68282576542fe13e67018254 | /rCode/scanExport.R | 06db8d24ec46324368a3ab12ce26ba501f668482 | [] | no_license | hsuanyuchen1/closestPoint | 4b78d6ef8f02809145ffa28b75930439e43caeb6 | b23529487ff24bd6688d5daa4a9b8023aa4848dc | refs/heads/main | 2023-01-03T12:48:13.104999 | 2020-10-27T08:02:47 | 2020-10-27T08:02:47 | 307,617,470 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,898 | r | scanExport.R | library(data.table)
library(magrittr)
library(geosphere)
library(sf)
library(dplyr)
source("closestPoint/rCode/findMinDist.R")
#sourceData is the 25mx25m CSV with whole taiwan data
scanExport = function(targetDir, sourceData, tempDir, outDir, successDir, failDir){
target <- fread(targetDir)
#move... |
93cb3b25b369a9da268c8c511c7eb8591e12ea6a | 91966e8ddddb3d5b542330ed6232eb89a83ea91a | /plot4.R | fcf7b5888b074436bc5505a8c5da84cd5757baea | [] | no_license | owl775/ExData_Plotting1 | b29dbe9914d14bc6cb05c0d1bb4c82f01b3e6b34 | 9ac69516d3b2e7ac1f6c340cc5fdc2f80631dda8 | refs/heads/master | 2021-05-17T01:45:26.969324 | 2020-03-27T20:34:33 | 2020-03-27T20:34:33 | 250,562,390 | 0 | 0 | null | 2020-03-27T14:55:13 | 2020-03-27T14:55:12 | null | UTF-8 | R | false | false | 1,566 | r | plot4.R | library(dplyr)
library(lubridate)
# read data file
data_file = 'household_power_consumption.txt'
power_consumption <- read.csv(data_file,sep=';', header=TRUE, na.strings = "?")
power_consumption$Date <- as.Date(power_consumption$Date, format="%d/%m/%Y")
# get subset of the data
start_date <- '2007-02-01'
stop_date ... |
1d6b270304fbb4ad716425da0f0cc2a90e777b22 | c8c610879e88ba7d6dd92c98ad13877b9d1979f3 | /sql_r/ar/coverage/insertIndirectPolygons.R | c09d8c0242eb9492deb5c46b51b84609aa4ce89d | [] | no_license | Telefonica/rural-planner | 7c14481cec0ba17de9d6d1a3637d41de92875cfe | c70226691ebeb2cec9591baf0df09b2f5f8e162e | refs/heads/master | 2022-11-27T08:38:50.751388 | 2020-08-13T15:56:34 | 2020-08-13T15:56:34 | 274,978,867 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,362 | r | insertIndirectPolygons.R | insertIndirectPolygons <- function(schema, indirect_polygons_table, infrastructure_table){
drv <- dbDriver("PostgreSQL")
con <- dbConnect(drv, dbname = dbname,
host = host, port = port,
user = user, password = pwd)
query <- paste0("INSERT INTO ... |
76e8c49b800e27a336d340d71527b7e0fb6da12b | 22d316e4dda53044ae7a6389c699f06baf673adf | /learning/MasterBlaster.R | 3d0bf8203ce0e5ed1275f10456e791e77a9e0351 | [] | no_license | sujaykhandekar/R_check | e454b396c8b354ce89086a3dde8e6f1a29179b13 | 00fa4571b93a0ffe63f0d685d2163d815aedb0ca | refs/heads/master | 2023-07-02T01:10:46.521824 | 2021-08-11T03:16:39 | 2021-08-11T03:16:39 | 390,935,115 | 0 | 1 | null | 2021-08-05T17:25:37 | 2021-07-30T04:55:02 | R | UTF-8 | R | false | false | 888 | r | MasterBlaster.R | # Author: Jitender Aswani, Co-Founder @datadolph.in
# Date: 3/15/2013
# Copyright (c) 2011, under the Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0) License
# For more information see: https://creativecommons.org/licenses/by-nc/3.0/
# All rights reserved.
library("RJSONIO")
rm (list = ls())
#... |
42d08f8b8e862526f4bb913162759bc8db57ba09 | a9729df11f1bf01a18d8a339a2915ce758118bc8 | /man/box_read.Rd | 058edd68022c26a6abd7ad2e0555c19e7f6919d2 | [
"MIT"
] | permissive | jilldwright56/boxr | ce5a651911d1aee50367aac9c9fa882ab4c91d7d | b81a6f7e821cb968788ccbbe45fbde6ba6e81705 | refs/heads/master | 2022-12-30T05:30:35.581815 | 2020-10-14T00:10:00 | 2020-10-14T00:10:00 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 4,260 | rd | box_read.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/boxr_read.R
\name{box_read}
\alias{box_read}
\alias{box_read_csv}
\alias{box_read_tsv}
\alias{box_read_json}
\alias{box_read_excel}
\alias{box_read_rds}
\title{Read an R object from a Box file}
\usage{
box_read(
file_id,
type = NULL,
ve... |
5f7fc9c06d9ca364e8c53afcca5454424b94c422 | fce81b75022c9153389ea279477c323e15d12926 | /datacommons/tests/testthat/test-popobs.R | 1aac5bad27d9b31fb46b0bb652caf3eb34a2f1e4 | [
"Apache-2.0",
"LicenseRef-scancode-generic-cla"
] | permissive | datacommonsorg/api-r | 5e9feea3efbbdd7333a84edc525156cae1ca7403 | f1c835dd3d8fe57183d3f441c04682b0e2f20a21 | refs/heads/master | 2021-08-17T17:39:32.734867 | 2020-07-06T05:17:19 | 2020-07-06T05:17:19 | 201,317,967 | 2 | 4 | Apache-2.0 | 2020-07-06T05:17:21 | 2019-08-08T18:46:32 | HTML | UTF-8 | R | false | false | 5,794 | r | test-popobs.R | # Copyright 2019 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, soft... |
a30a6d7430bd6a92758449d6112f64d5dde6d22a | 1d5128b54975c29b64d6f89ab2addf0573119d58 | /RegionPlot/demo/plotMCV.R | f31bb0963b634015726699faa57a100777a13fe9 | [] | no_license | Feng-Zhang/RegionPlot | 46d184eeef1fd0e096ae1409101f3740b84d54c1 | f959b882d80e58ef271ffe7a006714a6329f9927 | refs/heads/master | 2021-01-23T00:15:53.799614 | 2014-10-11T01:53:55 | 2014-10-11T01:53:55 | 23,922,954 | 1 | 1 | null | null | null | null | UTF-8 | R | false | false | 95 | r | plotMCV.R |
data(MCV_pval)
png("MCV.png", width=3200, height=2200,res=300)
plotRegion(MCV_pval)
dev.off()
|
647a25c70ab4fb885e7a5660250c832e489e07ea | e489df05b30305693071d9a070bfa954c4b63608 | /man/xbrlDoAllFun.Rd | 2d6065201e439401a16a05910e61269862b99b87 | [] | no_license | kossal/fundfi | fb2053925d8f6a7a2efce15c0a1c351247cc11b3 | 5905a9f5cd92af05af7242c951092b21b8d775bb | refs/heads/master | 2020-07-15T00:46:20.893168 | 2020-04-05T21:35:04 | 2020-04-05T21:35:04 | 205,440,019 | 0 | 0 | null | 2020-04-05T21:35:05 | 2019-08-30T18:53:04 | R | UTF-8 | R | false | true | 868 | rd | xbrlDoAllFun.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/xbrlDoAllFun.R
\name{xbrlDoAllFun}
\alias{xbrlDoAllFun}
\title{A mirror function of XBRL}
\usage{
xbrlDoAllFun(
file.inst,
cache.dir = "xbrl.Cache",
prefix.out = NULL,
verbose = FALSE,
delete.cached.inst = TRUE
)
}
\value{
A XBRL li... |
8bae8e476c813cb4b093127e38007360578ee6e9 | 3a5a3b4c51213b711e76a73c8cefae1b84c201ed | /R/gpHistPredict.R | 91b2e99ea89a9f4f7e53583b8d8e27e561cf8ec9 | [] | no_license | dennisthemenace2/gpHist | 88c616f9e3f47cd0cdeee30a9b67ed5865e2c27f | 51cae73bc157ac52eb48674d90d36adb44b0de62 | refs/heads/master | 2022-02-08T16:26:49.452782 | 2019-08-10T12:31:03 | 2019-08-10T12:31:03 | 72,182,422 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,177 | r | gpHistPredict.R | ##gpHistPredict
gpHistPredict =function(GP,X,x_pred){
# Make sure GP is right.
if(!is.list(GP) || is.null(GP$orders) || is.null(GP$alpha) ) {
print("gpHistPredict(): Object appears not to be a GP!")
return(NaN);
}
if ( ( ! is.matrix(X) ) || ( ! is.matrix(x_pred) ) ) {
print("gpHistPredict(): inp... |
97e8d113c6371cc52e4d4437355061b4d5eaec95 | a9fb5a228b2316e5b43f58e4b8d6c858cb7784f7 | /man/getCiceroGeneActivities-DsATAC-method.Rd | f041b3dc5c5ea6a2ab6144240ef9447e41a3fc0b | [] | no_license | GreenleafLab/ChrAccR | f94232d5ac15caff2c5b2c364090bfb30b63e61a | 43d010896dc95cedac3a8ea69aae3f67b2ced910 | refs/heads/master | 2023-06-24T05:29:29.804920 | 2023-03-17T13:01:49 | 2023-03-17T13:01:49 | 239,655,070 | 17 | 7 | null | 2023-05-05T09:51:23 | 2020-02-11T02:01:37 | R | UTF-8 | R | false | true | 1,256 | rd | getCiceroGeneActivities-DsATAC-method.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/DsATAC-class.R
\docType{methods}
\name{getCiceroGeneActivities,DsATAC-method}
\alias{getCiceroGeneActivities,DsATAC-method}
\alias{getCiceroGeneActivities}
\title{getCiceroGeneActivities-methods}
\usage{
\S4method{getCiceroGeneActivities}{DsA... |
105860969d2a36d59f6d49aaa6c0f584f1b73432 | e625a2afab25b28cc2a280b1cca965794b9ab78e | /plot4.R | a03dcd34bbc9d90904d6b8497a2f55e52a2a0435 | [] | no_license | rumbaugh/ExData_Plotting1 | 1ee5cbf1b43834565cddba2a4fe1099e69878cb5 | 0d30a76d92518483acc716a1d69f8e99a2c90f36 | refs/heads/master | 2021-08-22T20:52:48.801364 | 2017-12-01T08:13:46 | 2017-12-01T08:13:46 | 112,700,157 | 0 | 0 | null | 2017-12-01T05:47:14 | 2017-12-01T05:47:14 | null | UTF-8 | R | false | false | 1,762 | r | plot4.R | plot4 <- function(datapath = '.', outfile = 'plot4.png') {
## Creates a PNG plots of Global Active Power, Voltage
## Energy Sub Metering, and Global reactive power versus time
## in a 2x2 grid.
## Requires the file "household_power_consumption.txt". The path
## to this file must be given by datapath... |
86ed5915f5b0d9ebd614ed5a9d29a1c563ebb0d9 | 754d42490126fb8f2b0f505a92fff58972f59bbd | /R/classifyByGenesList.R | 4c41051d5d305731b003e76b0135ac81a213e3e1 | [] | no_license | federicocozza/geneticApproach | dac4b4ab3ef311cc1af1bbfa09ff77f5faf193fa | c276140e601b54009a0ce11385caccc1d581ff73 | refs/heads/master | 2020-04-10T02:29:40.662943 | 2018-03-21T12:29:28 | 2018-03-21T12:29:28 | 124,255,907 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,313 | r | classifyByGenesList.R | classifyByGenesList <- function(pythonPath,classType,genes,dataset,classLabels,core = 8, outer_fold = 3 ,inner_fold = 2){
temporanyDirectory <- getwd()
temporanyDirectory <- paste(temporanyDirectory,"/ImportantGenes",sep="")
temporanyDirectory_res <- paste(temporanyDirectory,"_res/",sep="")
dir.create(tempor... |
9f8440c1100a3c1bd5a6bb615c2f7711645ea027 | 08b4eaf203fbbe87b09fdb2dc96b5d11fff2c171 | /man/seurat_sample_tms_liver.Rd | ab541345033a7b3168e9505211893a0376f4ad21 | [] | no_license | cran/scDiffCom | a8f28d7f92acfba6b84e123707c437300a9adfd9 | 26fbcb29d53a04e49208cb38f3e515f4a59827aa | refs/heads/master | 2023-07-09T07:30:59.085372 | 2021-08-17T06:20:05 | 2021-08-17T06:20:05 | 397,309,543 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 913 | rd | seurat_sample_tms_liver.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data.R
\docType{data}
\name{seurat_sample_tms_liver}
\alias{seurat_sample_tms_liver}
\title{A down-sampled Seurat object to use for testing and benchmarking}
\format{
An object of class Seurat.
}
\usage{
data(seurat_sample_tms_liver... |
246cfedc64e4aae7ddf942efe4448e3322bd0da5 | c2e7ea15f6cae6b46b6a008423ff978ed474ce1c | /man/general.bar_plot_by.Rd | 4d748273bfd08f5e542da70236b08d11ca56239e | [] | no_license | jhooge/BioViz | 690b08804849438bfb3bdde29277c56cb89f5f9e | 1458724e59d4283ca9de9d0cd66543fb94422846 | refs/heads/master | 2021-01-23T07:56:03.244205 | 2017-08-10T09:59:17 | 2017-08-10T09:59:17 | 86,466,292 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 4,184 | rd | general.bar_plot_by.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/general.R
\name{general.bar_plot_by}
\alias{general.bar_plot_by}
\title{Function to create a barplot, with bars split by a second variable}
\usage{
general.bar_plot_by(freq, labels = NULL, labels.ab = NULL, file.name,
col = "tomato3", cex.l... |
3db4b1827a891cc9e7a67d96d8eb348b18121bfa | 3df348376d12e0c3d2d070c5a980809741639c5d | /R/tr_causal.R | 8b12b016a5796cfa8b84f739811c0465f180bb4a | [
"MIT"
] | permissive | bnicenboim/pangoling | a8d47e3c2677ce660b5d3917be8d5934a6598377 | 2a6855d5c51fa6e1ed2a723f309440a3df9379e6 | refs/heads/main | 2023-06-07T18:43:16.305506 | 2023-05-14T04:19:35 | 2023-05-14T04:19:35 | 497,831,295 | 4 | 0 | NOASSERTION | 2023-05-14T04:19:37 | 2022-05-30T07:17:10 | R | UTF-8 | R | false | false | 15,811 | r | tr_causal.R | #' Preloads a causal language model
#'
#' Preloads a causal language model to speed up next runs.
#'
#' A causal language model (also called GPT-like, auto-regressive, or decoder
#' model) is a type of large language model usually used for text-generation
#' that can predict the next word (or more accurately in fact to... |
78b69689c7140634de499bfbfc8fa31d33133908 | 2d34708b03cdf802018f17d0ba150df6772b6897 | /googlegamesv1.auto/man/RevisionCheckResponse.Rd | 7fa214c3079ef0789525875ce63088928d3e8964 | [
"MIT"
] | permissive | GVersteeg/autoGoogleAPI | 8b3dda19fae2f012e11b3a18a330a4d0da474921 | f4850822230ef2f5552c9a5f42e397d9ae027a18 | refs/heads/master | 2020-09-28T20:20:58.023495 | 2017-03-05T19:50:39 | 2017-03-05T19:50:39 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 661 | rd | RevisionCheckResponse.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/games_objects.R
\name{RevisionCheckResponse}
\alias{RevisionCheckResponse}
\title{RevisionCheckResponse Object}
\usage{
RevisionCheckResponse(apiVersion = NULL, revisionStatus = NULL)
}
\arguments{
\item{apiVersion}{The version of the API thi... |
ded1cfb2ef2e580738b12ab4c75861eb6b38c641 | 8c7d64d8a7519c8636de1448a52d8d2c74856665 | /cachematrix.R | 5bfe5d1a864959834cbf840c778159e7e3e96041 | [] | no_license | rwarrier4/ProgrammingAssignment2 | 44650bee0b85dd5cc457d51ff6fa200f95cead86 | c2048269ff2e12b6cd465c60399965eb0921216d | refs/heads/master | 2021-01-22T00:36:17.201739 | 2014-09-20T15:27:38 | 2014-09-20T15:27:38 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,400 | r | cachematrix.R | ## MakeCacheMatrix function creates a matrix and returns a list of functions
## to access and manipulate the matrix that you've created.
makeCacheMatrix <- function(x = matrix()) {
i <- NULL
geti <- function() i
## The set function is an alternative to creating the matrix using the m... |
c64a103894f6cdc0e9ed0cde15e02781710dbbe3 | 6ad337e2b26380a4ebf1ac301bb3e8aff19b846b | /R/CIT.R | e0d63013b36c09a1f434749e6aeef46309a9db3b | [] | no_license | kaseyriver11/k3d3 | 2824f2c078c2f0ba0659333b0bd68909442c4270 | 85c21f7725f6afe06a95d773716ddadff4386622 | refs/heads/master | 2020-12-29T02:44:20.607587 | 2017-06-04T22:56:11 | 2017-06-04T22:56:11 | 38,123,059 | 5 | 3 | null | null | null | null | UTF-8 | R | false | false | 2,145 | r | CIT.R | #' D3 Visualization: Collapsible Indented Tree
#'
#' Creates a collapsible indented tree.
#'
#' @param data the json file being used for the visualizations.
#' @param width width for the graph's frame area (in pixels) - default is null.
#' @param height height for the graph's frame area (in pixels) - default is null.... |
5c5a6ca9ca3de1d392f37d37b364e7e3baa37194 | a7cba5bed6b27f1c67f779a87a9b6f37462d761c | /man/plot_net_country.Rd | 27be11e4c742dc36c7620db8f928d765575ba04c | [] | no_license | ropensci/refsplitr | f75889011b59e24d736fda6492a6955c11f45860 | 38c01e609cbdf1ad28bc7c6a89de1e433892eb10 | refs/heads/master | 2023-05-22T20:59:33.245494 | 2022-02-07T17:25:38 | 2022-02-07T17:25:38 | 114,401,756 | 29 | 4 | null | 2022-02-07T14:26:19 | 2017-12-15T18:51:00 | R | UTF-8 | R | false | true | 1,877 | rd | plot_net_country.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/plot_net_country.R
\name{plot_net_country}
\alias{plot_net_country}
\title{Creates a network diagram of coauthors' countries linked by reference, #and
with nodes arranged geographically}
\usage{
plot_net_country(
data,
lineResolution = 10... |
7eea4094f99baf55dd9f99f5067fb53885366027 | d8fb86933d4bbe05a74f33b744686e92c479c420 | /R/rhub.R | db779ebf54c3f3d75f58ff0d45162f4c3e4e6cba | [] | no_license | cran/packager | 3bcb53591cc93ccff83578f0ad5f706caa253a49 | c41ba71a5517cd9b9e242bc29fd5fe9ef8795c69 | refs/heads/master | 2023-07-23T13:12:01.844282 | 2023-07-07T14:10:02 | 2023-07-07T14:10:02 | 242,503,192 | 1 | 1 | null | null | null | null | UTF-8 | R | false | false | 2,788 | r | rhub.R | ## #' Check on \code{rhub}
## #'
## #' Create rhub logs that will be queried using
## #' \code{get_local_rhub}, a helper function for
## #' \code{\link{provide_cran_comments}}.
## #' @template package_path
## #' @param os Character string specifying the operation systems to test on, stick
## #' with the default.
## #' ... |
65f4cab4db8214ca195fb768d642ea46758c2f9b | 4fe0f7d1d82290ba670fa0208436ff03f9159968 | /run_analysis.R | 6ccce0c244c1fdb07cdd3ea2f320ac58cd5df7ed | [] | no_license | twheelock1/Getting-and-Cleaning-Data-Course-Project | e9b729260fb8d6a118e3baa3d78eac09a676ab22 | 1391a670ebba6c81001bf621fc9f02063a07d036 | refs/heads/master | 2021-01-10T02:26:27.815038 | 2015-10-27T16:35:28 | 2015-10-27T16:35:28 | 44,923,953 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,913 | r | run_analysis.R | library(plyr)
subject_test <- read.table("UCI HAR Dataset/test/subject_test.txt")
x_test <- read.table("UCI HAR Dataset/test/x_test.txt")
y_test <- read.table("UCI HAR Dataset/test/y_test.txt")
subject_train <- read.table("UCI HAR Dataset/train/subject_train.txt")
x_train <- read.table("UCI HAR Dataset/train/X_train.t... |
1cea4e5821f8746afeeb349bf090240d775afa78 | d68578f6fc83ac88e2e41a0e735479e68796c1c9 | /R/utils.R | f2722a7554efb6d7dc6453d8b55b7a559230a9d3 | [] | no_license | anatolydryga/qiimeMap | a4413c4b036282a36e9b9af6f3cb0dcab30ac778 | 716e884d9bcd709bbf632a46e2bd908263439295 | refs/heads/master | 2021-01-20T10:35:55.170765 | 2014-11-13T17:17:06 | 2014-11-13T17:17:06 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 178 | r | utils.R | is_unique_ids <- function(data) {
ids <- unlist(data)
ids <- ids[! is.na(ids)]
len <- length(ids)
len_uniq <- length(unique(ids))
(len == len_uniq)
}
|
3b732589e6019db529c83c109604f459470eedac | b5e1392db0834e30f9ec914e5b757605f08d8a7f | /Chapter3/Redes/zcript_Fig3A.R | 85888095c9a49979a8aed9f0b0b3dfeb7094853a | [
"Unlicense"
] | permissive | aaleta/thesis_plots | 6226b180962cf3457b268496d0f1515d0c15364f | 58f2f2f7fc592234628e39ab90fff89763a19679 | refs/heads/master | 2022-12-17T03:50:56.104445 | 2020-09-25T00:21:07 | 2020-09-25T00:21:07 | 298,241,760 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,767 | r | zcript_Fig3A.R | library(ggplot2)
library(gridExtra)
library(grid)
library(ggthemes)
library(ggsci)
source("../../theme.R")
plotUER = function(print.plot=F)
{
#UUU
a = read.table("Data/UUU/diagramC_k6_mu0.10_ER.txt",header=T)
data = data.frame(gamma=a$gamma,beta=a$beta,id="sU6")
a = read.table("Data/UUU/diagramC_k12_mu0.10_ER.txt"... |
36b9b1872cd2ddbf6b40af03dfbd85a88e5d73ff | 3aef5a679c390d1f2c7ecba35eca09864164c5a5 | /R/tparams_mean.R | f470f1c99c4fba42e45a8320db70718b9c65ee2c | [] | no_license | jeff-m-sullivan/hesim | 576edfd8c943c62315890528039366fe20cf7844 | fa14d0257f0d6d4fc7d344594b2c4bf73417aaf3 | refs/heads/master | 2022-11-14T07:35:15.780960 | 2022-09-02T03:13:49 | 2022-09-02T03:13:49 | 140,300,858 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,695 | r | tparams_mean.R | # tparams_mean -----------------------------------------------------------------
#' Predicted means
#'
#' Create a list containing means predicted from a statistical model.
#'
#' @param value Matrix of samples from the distribution of the
#' mean. Columns denote random samples and rows denote means for different
#... |
63c0f017432a0012022f63307ecca413db818fed | 8c0faaeda764de080239adf03ba3e17192df48da | /02a-Utils.R | 4644b1e29d9be614c5dc2e9376925dc9f8739d11 | [] | no_license | HaydenMcT/Stat447-PokemonEggSteps | 8e409c3a6e6ed613dfd3559ff66914313430f00d | 9c3fcc9a420b3e7f2f20b39fa8d1cf719d3091be | refs/heads/main | 2023-04-10T20:02:17.484177 | 2021-04-15T18:36:23 | 2021-04-15T18:36:23 | 357,062,470 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 17,957 | r | 02a-Utils.R | ## CODE FILE 2a: Creates new Rdata object containing all utility functions needed for Phase B,
## and some for Phase C.
#' @description
#' Find category with modal probability
#' @param predMatrix ncases x J matrix; J is number of response categories
#' Each row of predMatrix is a probability mass function.
#' @ret... |
18e3db360b5ea9e0680e97332567bf17fcf3d78f | 3b41fce22a52127830f1dd69a56a6485d8ee0cd8 | /man/FindAlpha.Rd | 639117b11995bae03e3441408ed15014241bfb35 | [
"Apache-2.0"
] | permissive | cran/RegSDC | 165bbee727fc53149128a3e01e298cd535f25816 | ea50d6d5a35efd334df582d2a301c6a120bf1014 | refs/heads/master | 2022-08-29T08:12:12.653287 | 2022-08-19T07:30:02 | 2022-08-19T07:30:02 | 166,078,001 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 811 | rd | FindAlpha.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/CalculateC.R
\name{FindAlpha}
\alias{FindAlpha}
\alias{FindAlphaSimple}
\title{Calculation of alpha}
\usage{
FindAlpha(a, b, tryViaQR = TRUE)
FindAlphaSimple(a, b)
}
\arguments{
\item{a}{matrix E in paper}
\item{b}{matrix Eg i... |
8984a6820890f5ec2f5dcd8ba83c09ac8243d6f5 | fe3a2d4d2303c1302ab219a23d00828997cd5d12 | /rDNA/man/dna_dendrogram.Rd | 590a0f780ca1ebef342d85175540ced0ccfe9de4 | [] | no_license | njatel/dna | 2dfbb9e7b7d08c4e22d89191b5d726ca96e3b77c | 09a3e7aa3e13b5bf382365c7dee6d9a10d5e4ee9 | refs/heads/master | 2023-01-11T10:01:16.784668 | 2020-11-18T08:50:48 | 2020-11-18T08:50:48 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 18,317 | rd | dna_dendrogram.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/rDNA.R
\name{dna_dendrogram}
\alias{dna_dendrogram}
\title{Create a cluster dendrogram for a DNA database}
\usage{
dna_dendrogram(
connection,
statementType = "DNA Statement",
variable1 = "organization",
variable1Document = FALSE,
v... |
b7b41917ce155dce6d65bae29d097500e873d502 | 8f5bd879605797d1399cf4fb7bd15b8dff617649 | /src/1json_import.R | 271d1d841167e420a554ed75ef9cccf4f4a60e17 | [] | no_license | ryasmin/DHS_Data_Analysis | 40c45f2e12db24fb79bd3d209c2f710e1f742c4e | cd2291668d546dd748aeac1709b9b0a5def79f8f | refs/heads/main | 2023-03-10T04:55:39.666697 | 2021-02-16T20:08:00 | 2021-02-16T20:08:00 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 410 | r | 1json_import.R | library(rjson)
jsonRawPilot <- fromJSON(file= "json_data/PilotTest.json")
jsonRaw2_1 <- fromJSON(file = "json_data/Test2-1.json")
jsonRaw2_2 <- fromJSON(file = "json_data/Test2-2.json")
jsonRaw2_3 <- fromJSON(file = "json_data/Test2-3.json")
jsonRaw3_1 <- fromJSON(file = "json_data/Test3-1.json")
jsonRaw3_2 <- fromJSO... |
eab4549e141ff32ebaafc305b91d3c47ca5f29b2 | 2b0e7454e2c87076f4f97d35000bf3426b7d9aaa | /R/pub03_DatabaseOperationFuncs.R | ea09f40c75997079e421aefd53d2cf4a06a61113 | [] | no_license | raphael210/QDataGet | 52df9d791d7d1d8933555dbdfa9d81e42558a5ee | 83531020e180fe8d07fdfa4a75413fd2b95cd6b4 | refs/heads/master | 2020-04-12T06:29:33.198718 | 2019-02-01T07:50:14 | 2019-02-01T07:50:14 | 64,194,185 | 0 | 5 | null | 2017-03-16T03:29:45 | 2016-07-26T06:00:12 | R | UTF-8 | R | false | false | 77,474 | r | pub03_DatabaseOperationFuncs.R |
# ===================== xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx ======================
# ===================== Database Operation ===========================
# ===================== xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx ======================
#' defaultDataSRC
#'
#' get the default datasrc. You can reset the default value... |
92afa28b195e622abf278625fb4f53913035469f | 6e32987e92e9074939fea0d76f103b6a29df7f1f | /googleaiplatformv1.auto/man/GoogleCloudAiplatformV1Context.labels.Rd | a8384ddfb67c8d6130b9c58f9dbaddf21f14e0f8 | [] | no_license | justinjm/autoGoogleAPI | a8158acd9d5fa33eeafd9150079f66e7ae5f0668 | 6a26a543271916329606e5dbd42d11d8a1602aca | refs/heads/master | 2023-09-03T02:00:51.433755 | 2023-08-09T21:29:35 | 2023-08-09T21:29:35 | 183,957,898 | 1 | 0 | null | null | null | null | UTF-8 | R | false | true | 1,194 | rd | GoogleCloudAiplatformV1Context.labels.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/aiplatform_objects.R
\name{GoogleCloudAiplatformV1Context.labels}
\alias{GoogleCloudAiplatformV1Context.labels}
\title{GoogleCloudAiplatformV1Context.labels Object}
\usage{
GoogleCloudAiplatformV1Context.labels()
}
\value{
GoogleCloudAiplatfo... |
894b125498c45f94f68ea2b85fe1a5a51ba6b999 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/mgcViz/examples/check.gamViz.Rd.R | 317a0e368c7705ae97b29f3953309711667f2726 | [] | no_license | surayaaramli/typeRrh | d257ac8905c49123f4ccd4e377ee3dfc84d1636c | 66e6996f31961bc8b9aafe1a6a6098327b66bf71 | refs/heads/master | 2023-05-05T04:05:31.617869 | 2019-04-25T22:10:06 | 2019-04-25T22:10:06 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 529 | r | check.gamViz.Rd.R | library(mgcViz)
### Name: check.gamViz
### Title: Some diagnostics for a fitted gam model
### Aliases: check.gamViz
### ** Examples
library(mgcViz)
set.seed(0)
dat <- gamSim(1, n = 200)
b <- gam(y ~ s(x0) + s(x1) + s(x2) + s(x3), data = dat)
b <- getViz(b)
# Checks using default options
check(b)
# Change some alg... |
067d78bb12d6730ee128c5fbf0ed42747ed9ff05 | ed6dd1bb9c27ac987f12efbe59c784c1ae368bcb | /man/yhat.transform_from_example.Rd | 33036abdc34ddf84ae0b9e6a6eb08c97f0467be6 | [] | no_license | apatil/yhatr | 4efb1b3c155d96d39e0bca8b7a1f426218f0486c | 3296e47a3fef2f1298eeda4ee50f51bc2b1b8fca | refs/heads/master | 2020-12-25T21:24:06.805322 | 2015-03-12T18:20:34 | 2015-03-12T18:20:34 | 33,420,008 | 1 | 0 | null | 2015-04-04T20:52:54 | 2015-04-04T20:52:54 | null | UTF-8 | R | false | false | 774 | rd | yhat.transform_from_example.Rd | % Generated by roxygen2 (4.0.2.9000): do not edit by hand
% Please edit documentation in R/yhatR.R
\name{yhat.transform_from_example}
\alias{yhat.transform_from_example}
\title{Generates a model.transform function from an example input data.frame.
Handles columns which need to be type casted further after the initial J... |
c340dde9eaf0f2b36afa3deb457ab99160c03ef9 | 3b04bdd3babe0ac4cb0afb015b31d6d11d506e6c | /ArabMAGIC/R/zip_data.R | 9edcb130d67229bbc4c269ac57239332fdd9c867 | [] | no_license | kbroman/qtl2data | 21f4d43579cf681a4406766d9e4c780808346eea | 502f9627ecc72876d93de3b66439527ec3914536 | refs/heads/main | 2021-12-04T07:11:10.325235 | 2021-09-17T12:41:58 | 2021-09-17T12:41:58 | 43,719,321 | 0 | 0 | null | 2015-10-05T23:17:16 | 2015-10-05T23:17:16 | null | UTF-8 | R | false | false | 1,258 | r | zip_data.R | # zip the Arabidopsis MAGIC data, in two version (TAIR8 and TAIR9)
# - first subset the _geno and _foundergeno data to the markers with positions in the corresponding map build
library(qtl2)
set.seed(20190215)
tmpdir <- file.path(tempdir(), paste(sample(letters, 20, replace=TRUE), collapse=""))
tmpdir <- sub("//", "/... |
386b2c055d7204da855a6a5511029b3cf0b8dbbe | 0c6d2f47a296217105f38ae32ad5cf8e5deef1e2 | /man/inverseTAPE.Rd | 1cc5088ac2db4d6ff087a2b0a74a39bfec4889be | [] | no_license | cran/RFOC | 338616505b90e1f3c9511ae9b55a1d17f73d1bd6 | b2c97a028b6cf9802439a74d5a6140a3ce9d07e4 | refs/heads/master | 2021-06-01T20:24:37.900822 | 2018-01-18T10:13:23 | 2018-01-18T10:13:23 | 17,713,811 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,130 | rd | inverseTAPE.Rd | \name{inverseTAPE}
\alias{inverseTAPE}
\title{Inverse Moment Tensor
}
\description{Inverse moment tensor from
Tape angles.
}
\usage{
inverseTAPE(GAMMA, BETA)
}
\arguments{
\item{GAMMA}{Longitude, degrees
}
\item{BETA}{CoLatitude, degrees
}
}
\details{Uses Tape and Tape lune angles
to estimate the moment tensor... |
42f92d6c8d4ec6fd80ce43e95ae9a8c2f967ba0b | c0347fe541c2c95ea44ba8a69c595008b2f222d2 | /02_Rprogramming/Assignment3/best.R | 5820593af1fc9ebea0ca2732d4eefbeee5454955 | [] | no_license | MhAmine/DataScience_CourseraSpecialization | d0162e51459bf1e1daf4341d004d5546247a14eb | cd41c89915bba427870c73fe60fd80d02bbef6f0 | refs/heads/master | 2021-01-19T08:41:02.277035 | 2017-02-17T11:25:46 | 2017-02-17T11:25:46 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 926 | r | best.R | best <- function(state,outcome){
outcomes = c("pneumonia", "heart attack", "heart failure")
data <- read.csv("outcome-of-care-measures.csv", colClasses = "character")
if (!is.element(state, data$State)) {
stop("invalid state")
} else if(!is.element(outcome, outcome)) {
stop("invalid outcom... |
90e17ab4c4e1e89177139a14d1fd7f4ae7e98071 | c604c9c916065e77196f041dad992886aa55b72a | /plot3.R | 791b4585195f4995db41028835aa4b5ab3890925 | [] | no_license | astropic/ExData_Plotting1 | cae3e42f06558f7af7f75a5f9c7db808089c5f15 | 9acef41c197e388f1f67bb1f49b80d2a70eccf7d | refs/heads/master | 2021-01-22T06:58:30.888921 | 2016-04-09T13:23:30 | 2016-04-09T13:23:30 | 55,845,319 | 0 | 0 | null | 2016-04-09T13:20:04 | 2016-04-09T13:20:03 | null | UTF-8 | R | false | false | 1,087 | r | plot3.R | # Make sure time locale is English
Sys.setlocale("LC_TIME", "English")
# Read and subset data. NA is represented by "?".
data <- read.csv("household_power_consumption.txt", sep=";", na.strings="?")
sub_data <- subset(data, data$Date == "1/2/2007" | data$Date == "2/2/2007")
# Join Date and Time columns into a D... |
ffa29abb3fa77e74f3fa4a879afe49ba419e3f39 | 2d34708b03cdf802018f17d0ba150df6772b6897 | /googledataprocv1alpha1.auto/man/JobScheduling.Rd | 3785e95a03eb9e9db6ab005143a670588067da5a | [
"MIT"
] | permissive | GVersteeg/autoGoogleAPI | 8b3dda19fae2f012e11b3a18a330a4d0da474921 | f4850822230ef2f5552c9a5f42e397d9ae027a18 | refs/heads/master | 2020-09-28T20:20:58.023495 | 2017-03-05T19:50:39 | 2017-03-05T19:50:39 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 694 | rd | JobScheduling.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/dataproc_objects.R
\name{JobScheduling}
\alias{JobScheduling}
\title{JobScheduling Object}
\usage{
JobScheduling(maxFailuresPerHour = NULL)
}
\arguments{
\item{maxFailuresPerHour}{Optional Maximum number of times per hour a driver may be rest... |
9c12cf2bb0965483f68716ae27fe5b5880113869 | a153380b0bd7f9d10ac4e8d53e2a8238daf34b2a | /man/get_scores_and_T_by_score.Rd | 100e631e6096c8b8632188dadff383b2926c9b47 | [] | no_license | gostevehoward/uniformrank | f31a915a25c39fd750af07dd4c5e0a60ca270e39 | 1f207c8abf1017d4d1e1c596304059d44c20d945 | refs/heads/master | 2022-09-02T00:34:45.562763 | 2020-05-31T04:01:45 | 2020-05-31T04:31:39 | 268,208,116 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 1,146 | rd | get_scores_and_T_by_score.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/internal.R
\name{get_scores_and_T_by_score}
\alias{get_scores_and_T_by_score}
\title{Generate the score for each pair difference and the observed
value of the random walk T using the raw pair differences and
the score function. Not meant to b... |
17223ad89f2408cb5afbedb5a207ff563eb571c0 | d7471f659e9d6e2293f6a5b880bd8fad7ea653c0 | /code/scripts/init.R | 70f81312c7e291b4c3dcc65a3acb1c69c3fda8d5 | [] | no_license | mabafaba/mse_sr | 113d792e9990ed98b1f2ee8de9e0e4c34d274ee5 | 2a4ff98545ae6b5525d939691441979d63bb7ff1 | refs/heads/master | 2021-01-18T23:10:57.819898 | 2017-11-27T13:00:12 | 2017-11-27T13:00:12 | 87,091,632 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,043 | r | init.R | setwd("/Users/m/paper_january17")
src<-"./code/data/all_LU.shp"
require("rgdal")
require("raster")
require("abind")
require("gdalUtils")
require("MASS")
source("./code/scripts/load_data.R")
source("./code/scripts/make_data.R")
source("./code/scripts/prep_data.R")
source("./code/scripts/analysis.R")
source("./code/scrip... |
6faf6e2a772a6a007363d9933df9d686e95ecd99 | a225f28de5ac8e3c47fd7b522957400d725b0ce4 | /R/general_seq_fun.R | d19cda5e7a01d0f70f512d8b6ee8680aa5a3796a | [] | no_license | cran/SeqBayesDesign | 5f1b73109b73befb620811ad7c417d9c1cac5825 | ccc2ee8ac2d904ab9f84fc06d6e597385f3901c1 | refs/heads/master | 2021-01-25T11:39:14.257819 | 2018-03-01T08:32:38 | 2018-03-01T08:32:38 | 123,413,990 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 37,348 | r | general_seq_fun.R | #library(MASS)
### data input ###
#' @export
data.read <- function(filename, exp.type = c("ALT", "CFT.EC"), ...) {
### the file is coded that c(stress levels, failure time, censored, weight)
if(class(filename) == "character"){
res <- read.csv(file = filename, ...)
}else if(class(filename) == "data.frame"){
... |
ab13b252aa778b4e3f53fb9724d9a848ed8e695a | 1e36964d5de4f8e472be681bad39fa0475d91491 | /man/SDMXUtilityData.Rd | 9d27f3d06f8c30bdf1d0004f0ba23797d0bfc74a | [] | no_license | cran/rsdmx | ea299980a1e9e72c547b2cca9496b613dcf0d37f | d6ee966a0a94c5cfa242a58137676a512dce8762 | refs/heads/master | 2023-09-01T03:53:25.208357 | 2023-08-28T13:00:02 | 2023-08-28T13:30:55 | 23,386,192 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 929 | rd | SDMXUtilityData.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/Class-SDMXUtilityData.R,
% R/SDMXUtilityData-methods.R
\docType{class}
\name{SDMXUtilityData}
\alias{SDMXUtilityData}
\alias{SDMXUtilityData-class}
\alias{SDMXUtilityData,SDMXUtilityData-method}
\title{Class "SDMXUtilityData"}
\usa... |
0ac5c2344508ceffbda139ed9903445e3696c04a | ea9348a94cb36ae70c2737e49ae03f6301be8ba1 | /data_analysis_course/videogames.R | 9ad453ba84ea9b4e8a0f06c35f32fd0fd333b703 | [] | no_license | quantum-pie/r-scripts | 84cb82abc034a40b82e36dc970b66fbc2b55dea2 | d3ba08a1a10c5b7c626018d7c43727deb459f74d | refs/heads/master | 2020-12-24T09:29:54.573394 | 2018-07-26T14:18:14 | 2018-07-26T14:18:14 | 73,291,113 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,687 | r | videogames.R | library(ggplot2)
library(dplyr)
library(forcats)
library(tidyr)
data <- read.csv("r-github/vgsales.csv")
# overall look
overall_data <-
data %>%
mutate(Year = strtoi(Year)) %>%
select(Year, Global_Sales, Platform) %>%
filter(Platform %in% c("PS", "PS2", "PS3", "PS4", "XB", "X360", "XOne"), !is.na(Year)) %>%
... |
c9a93daaf761c0d5681618492335ccc43275d2e7 | 97fdd3114a09ce6b6f87e58487c2e2ba06b287f6 | /connect_to_Db.R | 2e57758242367614de838095084864b8150f6233 | [] | no_license | NathanJablonski/Formulations | 46c19efed98a488bb0159fa74647fac216e8dee0 | 0107de1112dc047993efa074d9e192570c3853c3 | refs/heads/master | 2022-11-17T08:09:27.410621 | 2020-07-14T19:46:49 | 2020-07-14T19:46:49 | 273,584,613 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 703 | r | connect_to_Db.R | ##------------------------------------------------------------------------------
# Function: connect_to_Db
# Desc: sets up a database connection
# Parameters:
# In: raw text
# Out:
# Returns: text without space characters
##-------------------------------------------------------------------------------
connect_t... |
0f1f5cb1e0ab92226eaa93d33f1eb5c5178e1616 | 2bec5a52ce1fb3266e72f8fbeb5226b025584a16 | /mosum/man/mosum.pValue.Rd | 1d4805143feff3afdaee4048de23eb3d6aa67489 | [] | no_license | akhikolla/InformationHouse | 4e45b11df18dee47519e917fcf0a869a77661fce | c0daab1e3f2827fd08aa5c31127fadae3f001948 | refs/heads/master | 2023-02-12T19:00:20.752555 | 2020-12-31T20:59:23 | 2020-12-31T20:59:23 | 325,589,503 | 9 | 2 | null | null | null | null | UTF-8 | R | false | true | 624 | rd | mosum.pValue.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/mosum_test.R
\name{mosum.pValue}
\alias{mosum.pValue}
\title{MOSUM asymptotic p-value}
\usage{
mosum.pValue(z, n, G.left, G.right = G.left)
}
\arguments{
\item{z}{a numeric value for the observation}
\item{n}{an integer value for ... |
957bb655a7013041f3187dacc143efc5789ad55c | bd406d9bc18f29fc5397fffede48d621d91c3184 | /cachematrix.R | cb94ac423524397718157db8d3ae61865ae57b93 | [] | no_license | XinyuZhengDeveloper/JHUcoursera_datascience | cf6af9053c19bd0213b9c9a9f179069dc646edde | 5b9f4e788dfd625e9591508833471c196c608cc2 | refs/heads/master | 2022-09-09T12:11:11.158279 | 2020-05-27T15:09:17 | 2020-05-27T15:09:17 | 267,349,880 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 839 | r | cachematrix.R | ## The function is to cache the inverse of a matrix.
## functions do
## this function create a matrix cache its inverse
makeCacheMatrix <- function(x = matrix()) {
i<-NULL
set<- function(y){
y<<-x
i<<-NULL
}
get<-function()x
set_inverse<-function(inverse) i<<-inverse
get_inverse<-function() i
li... |
5f3e7b08121ecfd4764cc261468b16151f917be4 | cec9144da1e7568b8e3d474e75cbae5222fadb8e | /man/help.Rd | 14aaca1933966a2b564412789586058c98cc8caf | [] | no_license | jimhester/types | 9055cd34389861af80b3c9cfc3417eb1a90303d4 | 7251e82d1d6a6996feef1566892e895f9ebfb2ab | refs/heads/master | 2020-07-25T12:51:15.511091 | 2016-11-30T21:43:08 | 2016-11-30T21:43:08 | 66,026,087 | 90 | 2 | null | 2016-11-30T21:43:08 | 2016-08-18T19:49:22 | R | UTF-8 | R | false | false | 239 | rd | help.Rd | \name{?}
\alias{?}
\title{Documentation Shortcuts}
\usage{
"?"(e1, e2)
}
\arguments{
\item{e1}{The type of documentation}
\item{e2}{The topic of documentation}
}
\description{
Documentation Shortcuts
}
\seealso{
\code{\link[utils]{?}}
}
|
8d8b75034fdca33a687139488ec5f4964a0bf91a | bb275dc2cd2e7c722ac17938d2e5fa68af3bce97 | /tests/testthat/test-summarize_across.R | dc9054d0e3bcb4c244c312f4a414aeffea5ea47b | [
"MIT"
] | permissive | timjaya/tidytable | 8ba648689162842fdb4aa7f5153d16d62895ece5 | ea653f6260dafc9f1bda01ff40cf3b9eda3d72c0 | refs/heads/master | 2022-11-05T00:09:58.604231 | 2020-06-23T00:34:19 | 2020-06-23T00:34:19 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,166 | r | test-summarize_across.R | test_that("single function works", {
test_df <- tidytable(a = 1:3, b = 4:6, z = c("a", "a", "b"))
result_df <- test_df %>%
summarize_across.(c(a, b), mean, na.rm = TRUE)
expect_named(result_df, c("a", "b"))
expect_equal(result_df$a, 2)
expect_equal(result_df$b, 5)
})
test_that("summarise spelling works... |
a5e9b070264b9ebd5b10950ed86d6adcf63c4939 | aa180339fe5d6c0b6bb3bac86a72c5ebf65c60a4 | /rTTManApi/R/R/TradeHistory.R | e6c5c09e21658a2150898a7efda489c9ddb5e883 | [] | no_license | SoftFx/TTManagerAPI | 7ad6f66fd269f89125ebd9757bb65fea10a3ff05 | f4eab7d678e5fb27bbebc459409505d4526cc298 | refs/heads/master | 2023-07-20T10:08:55.744338 | 2023-07-05T16:03:36 | 2023-07-05T16:03:36 | 95,440,101 | 0 | 2 | null | 2017-07-24T17:59:42 | 2017-06-26T11:35:27 | C# | UTF-8 | R | false | false | 22,572 | r | TradeHistory.R | #' Gets the Trade reports as requested
#'
#' @param accId a numeric vector. Accounts ids.
#' @param from a POSIXct object. Start time. By default, from = ISOdatetime(1970,01,01,0,00,00, tz ="GMT").
#' @param to a POSIXct object. End time. By default, to = ISOdatetime(2017,08,01,0,00,00, tz ="GMT").
#' @param transTypes... |
b0436b6f88743b7e129b29f8b39796088bdc028a | ed0ffe8895fef2f342e333b5019f539a57e3cba6 | /concepts/numeric_interactions_setup.R | f639ea2bd1149a5503330c64bd4056bdcc2ca71a | [] | no_license | tjvananne/kaggle_zillow | 7072a0ee83173ff7170da8a1824082e705754191 | 3151121fb8dd82a8642e1049fe7d836add5fe488 | refs/heads/master | 2021-01-23T21:45:54.131133 | 2017-10-16T04:34:32 | 2017-10-16T04:34:32 | 102,903,846 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 11,348 | r | numeric_interactions_setup.R |
# testing the setup of multiple interactions
library(gtools) # <-- combinations and permutations (for column name combos)
library(assertthat) # <-- for testing
library(xgboost) # <-- for testing the creation of DMatrices
library(caret) # <-- for easier scaling
# example with iris data:
df <- head(iri... |
a856804067dee063c51966b3bb2d6c53f09984f6 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/qdap/examples/paste2.Rd.R | e40974cb5d9d8a374c77e0c08022910b78ac40ff | [] | no_license | surayaaramli/typeRrh | d257ac8905c49123f4ccd4e377ee3dfc84d1636c | 66e6996f31961bc8b9aafe1a6a6098327b66bf71 | refs/heads/master | 2023-05-05T04:05:31.617869 | 2019-04-25T22:10:06 | 2019-04-25T22:10:06 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,083 | r | paste2.Rd.R | library(qdap)
### Name: paste2
### Title: Paste an Unspecified Number Of Text Columns
### Aliases: paste2 colpaste2df
### Keywords: paste
### ** Examples
## Not run:
##D ## paste2 examples
##D v <- rep(list(state.abb[1:8], month.abb[1:8]) , 5)
##D n <- sample(5:10, 1)
##D paste(v[1:n]) #odd looking return
##D pas... |
dc155b7ef202cace10bdb830b03092335e42418f | f245521e63b59e37470070092b7d1d38a87b2e48 | /libs/plotAA.r | 1f93740e03c91e8bfcd7862d7ffa61d20aa2c2c0 | [] | no_license | douglask3/UKESM-land-eval | 3c10d10eba32bcef1e7b2a057db3b22fdf2fd621 | aad3f6902e516590be02585ad926bfe1cf5770bf | refs/heads/master | 2021-08-17T06:32:10.736606 | 2021-07-14T12:57:13 | 2021-07-14T12:57:13 | 242,747,830 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,063 | r | plotAA.r | limits_aa = c(0, 0.1, 0.2, 0.5, 1, 2, 5)
aa_cols = c('#ffffe5','#f7fcb9','#d9f0a3','#addd8e','#78c679','#41ab5d',
'#238443','#006837','#004529')
plotAA <- function(r, lab = '', name = '', units = '',
cols = aa_cols, limits = limits_aa, regions = NULL,
... |
4ef4cc4636df45cc46c32b387e1c519035507e68 | 68e1ac98bf1c17a77f1074bf190e1acb763df791 | /R/plotGeneBarPlot.R | 75845142dae6775cb9df24097299cfc78e03f8af | [
"MIT"
] | permissive | mukundvarma/pledger | db4656ce07140354f2bc65c65e04962fe57f3013 | c41a865a541dc5038d0ebe7b7f2766abf4ad1b7b | refs/heads/master | 2021-05-15T22:28:26.458772 | 2017-10-12T21:31:14 | 2017-10-12T21:31:14 | 106,713,748 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,124 | r | plotGeneBarPlot.R | #' Barplot for gene expression values
#'
#' plotGeneBarPlot takes as input a counts matrix (or dataframe), a metadata dataframe
#' and the names of two metadata variables to plot a barplot with error bars of expression
#' values grouped along the x axis and with different fill colors to show
#' summarized expression of... |
d3599674b63c15837356037b7b59ca5e7ab06e97 | 08ea0442af72551490a4a8e5107ed0c752c3299f | /R/GC.adjust.R | dc5117c28458d4ac0d9364762538f3cd4f96fd08 | [] | no_license | cran/saasCNV | baaf78e61e70af648ffdf220f63e03771c53e7a6 | 2b74d199913425db6929decc04118ebbd55b1803 | refs/heads/master | 2020-12-31T04:56:39.453872 | 2016-05-18T02:04:56 | 2016-05-18T02:04:56 | 59,067,822 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,068 | r | GC.adjust.R | GC.adjust <-
function(data, gc, maxNumDataPoints = 10000)
{
data$marker <- paste0(data$chr, ":", round(data$position/1000,0)*1000+1)
gc$marker <- paste0(gc$chr, ":", gc$position)
data <- merge(x=data, y=gc[,c("marker","GC")], by="marker", all=FALSE)
data <- data[order(data$chr, data$pos),]
data <- ... |
ba83053f7b3b09c74e49dc0924f0664a324dfe17 | 9a8d950e524c52daf2baf77b84aaef20b3b64bdc | /Clean and Merge Waves 1-4.R | 7e6b7520d8ffb9d6c2245c6b9625e31e4354acba | [] | no_license | tylerleigh94/Prep-for-Wave-5 | be4f20132a7e3eca7a1577691b68a0765f893426 | db24204e30d49fc3046b41782d28a0276f945f0d | refs/heads/master | 2020-09-08T23:07:51.476955 | 2019-11-23T16:44:17 | 2019-11-23T16:44:17 | 221,271,418 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,272 | r | Clean and Merge Waves 1-4.R | ####Libraries####
library(easypackages)
libs<-c("tidyr", "dplyr", "car", "haven")
libraries(libs)
####Read in Data####
dat.1 <- read_sav("Data/wave1 clean.sav")
dat.2<- read_sav("Data/wave 2 cleaned.sav")
dat.3 <- read_sav("Data/wave 3 cleaned.sav")
dat.4 <- read_sav("Data/wave 4 cleaned.sav")
####Merge Datasets togeth... |
7ea24f0d578b294da28fbc2f9426e977b28e59b0 | 17dc451c33b8726441d03b1d604d7e6ed4a984b8 | /R/ConvertSexFormat.R | d7f33455c16ba1bf5491468f580cfcca66b4bf32 | [] | no_license | TWilliamBell/angler | ad8d57bb3b902a0e87b20b9b3f8e2844c7cefd1d | ffa59d8aa92e256b673423c5572c3136ae37e53f | refs/heads/master | 2022-03-12T16:29:48.936809 | 2022-03-03T17:00:11 | 2022-03-03T17:00:11 | 140,886,555 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 846 | r | ConvertSexFormat.R | #' Convert Sex Data to format used by our Functions
#'
#' @param Sex A character or factor vector (vector produced will be the same type) that includes the sex of each individual.
#' @param female.string How sex for females is recorded currently (defaults to "F").
#' @param male.string How sex for males is recorded cur... |
b74aba3d1b04a70e9d134cb8b8ff81b45a474a0b | 8595bf1f5409b247a416e3d313f922e1c1425968 | /code/CalculatePredictionMetrics.R | d5c016c65fc797686dc1abe7e23213a682f5619e | [] | no_license | srp33/BCRiskPathways | 29a88ff38ac1f50e559bcf0a835058d8abd2f0ce | fa9cb603373a196d1370bd8ffd4b5d7d883f41de | refs/heads/master | 2021-01-19T03:10:14.984908 | 2015-12-29T14:55:05 | 2015-12-29T14:55:05 | 31,468,999 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,534 | r | CalculatePredictionMetrics.R | inFilePath = commandArgs()[7]
targetClass = commandArgs()[8]
numPermutations = as.integer(commandArgs()[9])
outActualFilePath = commandArgs()[10]
outEmpiricalFilePath = commandArgs()[11]
suppressPackageStartupMessages(library(ROCR))
#suppressPackageStartupMessages(library(rms))
calcAuc = function(actual, prob)
{
pr... |
c2696ef3f8f4c6938597d6f23583219ab137a9b7 | 04bf444bf40498ba6672d8558b6aac2e7b2c8031 | /tidyabs.R | a116a31d9651d6ac02bac88716c8b60d3db4f314 | [] | no_license | triadicaxis/quickr | dea5bb836dce9ece41c614db002bf7477f0a70e2 | 784723c3ac9a43304257788abcd7d0a2dc2e066a | refs/heads/master | 2020-03-11T11:10:19.392031 | 2019-10-21T14:54:12 | 2019-10-21T14:54:12 | 129,503,198 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,071 | r | tidyabs.R | # install.packages("devtools")
# install.packages("readabs")
# devtools::install_github("ianmoran11/tidyABS")
#####################################################################
library(tidyABS) ## Ian Moran
library(readabs) ## Matt Cowgill
library(tidyverse) ## Hadley Wickham
#####################################... |
f2257e9807bce5895ee4e946caa0e087eda1c9cb | ee8733c46c91949478b44143e4977ca0ca857968 | /man/vim.norm.Rd | 85cf4c11e2a7a614bb8e918579297bae543e7d52 | [] | no_license | holgerschw/logicFS | 0a7919ef1012814b83a114dbc485e8be3d21e7ae | ed8b0be37da919754b39e1a46e793e253b06ddaf | refs/heads/master | 2021-06-06T01:10:52.594711 | 2020-04-12T21:34:42 | 2020-04-12T21:34:42 | 148,649,928 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 5,278 | rd | vim.norm.Rd | \name{vim.norm}
\alias{vim.norm}
\alias{vim.signperm}
\title{Standardized and Sign-Permutation Based Importance Measure}
\description{
Computes a standarized or a sign-permutation based version of either the Single Tree Measure,
the Quantitative Response Measure, or the Multiple Tree Measure.
}
\usage... |
930dbb0ffff1f9b17d7a42703024af40464208a8 | 768270fa492cd7b2e18c6a333fdea9fecdc15fa8 | /G4013/Lec7-multReg2.R | f1593aa167071af336bcb07ca5b65fcf20b9a51c | [] | no_license | xw2239/QMSS-R-Code | 2dc3ec24d92fc320f6f94b70b4d272210058c170 | c7a62422a3724f870a9874ee7cf44b8776d5e2b0 | refs/heads/master | 2021-01-17T14:23:45.052722 | 2013-10-13T03:46:43 | 2013-10-13T03:46:43 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 8,859 | r | Lec7-multReg2.R | # ---------------------------------------------------------
# Title: Multiple Regression 2
# R version: 3.0.0 (2013-04-03) -- "Masked Marvel"
# R Studio version: 0.97.336
# OS: Mac OS X 10.7.5
# Author: Eurry Kim <ek2758@columbia.edu>
# Maintainer: Eurry Kim <ek2758@columbia.edu>
# Description: G4013 Lecture 7
# ----... |
7ecf3125e2bc71197c58e07c8835f06a97c49856 | 91c17f2f5a3580c515df608a1531e5d258a6f9b4 | /miso_rmats.R | 1e37fbc60ac9efef40f680856be81dcf58b1b835 | [] | no_license | rnasys/PRMT_interactome | ea1e74c0d8e5dcbb54ea1e26684271e657d1cd11 | 66b45744e1f99b91ec890abd4fe50800f82ef581 | refs/heads/master | 2022-10-07T03:59:00.132026 | 2020-06-12T21:07:55 | 2020-06-12T21:07:55 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 21,666 | r | miso_rmats.R | library(RMySQL)
library(stringr)
library(RColorBrewer)
library(ggplot2)
library(reshape2)
library(biomaRt)
library(future.apply)
library(pheatmap)
library(GeneOverlap)
library(venn)
library(Cairo)
library(plyr)
library(DBI)
library(pool)
#data breaks according to the quantile
quantile_breaks <- function(xs, n = 10) {... |
8c9210898dc3d376ffc67a5a56f08d36aef9ea9d | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/pRolocdata/examples/groen2014.Rd.R | c25e03e77740cae6b0964840ddeefca76a21ce2c | [] | no_license | surayaaramli/typeRrh | d257ac8905c49123f4ccd4e377ee3dfc84d1636c | 66e6996f31961bc8b9aafe1a6a6098327b66bf71 | refs/heads/master | 2023-05-05T04:05:31.617869 | 2019-04-25T22:10:06 | 2019-04-25T22:10:06 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 731 | r | groen2014.Rd.R | library(pRolocdata)
### Name: groen2014
### Title: LOPIT experiments on Arabidopsis thaliana roots, from Groen et
### al. (2014)
### Aliases: groen2014 groen2014r1 groen2014r2 groen2014r3 groen2014cmb
### groen2014r1goCC
### Keywords: datasets
### ** Examples
data(groen2014r1)
data(groen2014r2)
data(groen2014r3... |
3583bf8d44137bd50d60667099263f4985025fab | 7a667a26aa13315da508003bc71b285a2032e00c | /man/cocoSetLogLevel.Rd | 2529caa1ff1357e3d2e84e0d1d79344057db9d3e | [
"BSD-2-Clause"
] | permissive | berndbischl/rcoco | 973bf74aaf3899961eb7137479f92f836c0d7a6e | 848a862c0cbe583831853a978de6adc932c20b5f | refs/heads/master | 2021-01-23T03:13:30.287541 | 2017-06-22T12:55:04 | 2017-06-22T12:55:04 | 86,060,085 | 3 | 1 | null | 2017-06-22T09:54:07 | 2017-03-24T11:17:20 | C | UTF-8 | R | false | true | 449 | rd | cocoSetLogLevel.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/cocoSetLogLevel.R
\name{cocoSetLogLevel}
\alias{cocoSetLogLevel}
\title{Set log level for coco platform.}
\usage{
cocoSetLogLevel(level = "info")
}
\arguments{
\item{level}{[\code{character(1)}]\cr
Log level, can be \dQuote{debug}, \dQuote{in... |
bd2c2f1b4437150ca292e2faf075f4139ce80bcc | 46450b27a8693ebba08bdd88f46d9d9dee4c10d4 | /CSB 2018 Final Project Chris Lee/get_AUC_of_Samples.R | d41b96d1eabaeaf22be5868a4c4e3060175664e6 | [] | no_license | ChrisLeeUchicago/CSB-2018-Project | ee17ddc66ff09cf03b8beac56c6903a437a47108 | c7a0497cc2bf023bfbf277f3369fc163540e0998 | refs/heads/master | 2021-09-09T00:23:47.577374 | 2018-03-12T22:37:53 | 2018-03-12T22:37:53 | 124,698,683 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,911 | r | get_AUC_of_Samples.R | #this portion of the code directly follows from the get carbonyl and get OH signal functions
#it assumes that the global environment contains the carbonyl and OH signal data
#for this part, we'll need the package zoo so we'll need to install and load it
install.packages("zoo")
#if zoo is already installed, we just nee... |
662805faf3acc23d64853845aec6c1c60fd5bc7a | 495ebf2ec08b9fabdaa689c7b9aa8bedd168a022 | /man/ExploreModelMatrix.Rd | 94fd132ee567a0a7ab2cdf136df24c8406779600 | [
"MIT"
] | permissive | csoneson/ExploreModelMatrix | bec8a9556beaa4bd906b5a8eb777fcc2f8470f50 | 5ec1ff318756631c4e1235457f5b41582dfe4580 | refs/heads/devel | 2023-05-25T18:55:09.510113 | 2023-05-13T07:39:31 | 2023-05-13T07:39:31 | 195,576,287 | 37 | 2 | NOASSERTION | 2023-04-22T18:53:05 | 2019-07-06T19:32:33 | R | UTF-8 | R | false | true | 1,285 | rd | ExploreModelMatrix.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ExploreModelMatrix.R
\name{ExploreModelMatrix}
\alias{ExploreModelMatrix}
\title{Explore model matrix}
\usage{
ExploreModelMatrix(sampleData = NULL, designFormula = NULL)
}
\arguments{
\item{sampleData}{(optional) A \code{data.frame} or \code... |
37cd05f764b304e21401f5a1aa40932993502708 | 1a5910e469aaa076b8d8f59577b4be6afbf5a054 | /plot1.R | 95ed885c1d0c9268fbb60a633b143ce5f52866b1 | [] | no_license | sshariqrizvi/ExData_Plotting1 | ac5e1ba6db6025e90632c014fe0163681629bce9 | ab01ebff9cc80a6a82988a3ac5e5f9dda0e57e5c | refs/heads/master | 2021-01-21T05:40:35.409819 | 2015-07-12T22:27:53 | 2015-07-12T22:27:53 | 38,972,410 | 0 | 0 | null | 2015-07-12T18:15:43 | 2015-07-12T18:15:43 | null | UTF-8 | R | false | false | 650 | r | plot1.R | if(!exists("mydata"))
{
colClasses <- c("character","character",rep("numeric",7))
mydata <- read.csv("household_power_consumption.txt", header = TRUE, sep = ";", na.strings="?", colClasses=colClasses)
mydata$DateTime <- strptime(paste(mydata$Date, mydata$Time), "%d/%m/%Y %H:%M")
mydata$Date = as.Date(mydata$Da... |
b9eec523ffdab6affdb781322862c40bff4805ba | e3837eaf2c65c74c0e01ad395dd39373ba5eafba | /src/gpdream/modules/Inferelator/src/main.R | c9cb4cd57da6a72dc5ab2d53cd4bb3afd26f6b74 | [
"MIT"
] | permissive | kevintee/Predicting-Gene-Networks | 907df99b37e7de29db79ff041856e37fed06b949 | bf415f2b11cd7289b13ab900752cf1f856ce4b47 | refs/heads/master | 2020-06-01T11:28:44.124804 | 2015-05-06T06:52:25 | 2015-05-06T06:52:25 | 31,395,188 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 13,037 | r | main.R | ## .-.-. .-.-. .-.-. .-.-. .-.-. .-.-. .-.-. .-.-.
## /|/ \|\ /|/ \|\ /|/ \|\ /|/ \|\ /|/ \|\ /|/ \|\ / / \ \ / / \ \
##`-' `-`-' `-`-' `-`-' `-`-' `-`-' `-`-' `-`-' ' '
## May th17
## Bonneau lab - "Aviv Madar" <am2654@nyu.edu>,
## NYU - Center for Genomics and Systems Biology
## .-.-.... |
cb5f08405b699af0ca4f02a04fd15929a2643035 | a85284bff5a7cb382e737d2aad40c1429c458741 | /R/straf.R | d29bf60cbaa986e76ce6a9180a9d1134d5253975 | [] | no_license | asitav-sen/straf | 0db902e187b78d0c17d570a866dbf6d5f407698e | aac57d4566624bd3408e85fb31aded0eaf6f4ed1 | refs/heads/master | 2023-04-19T23:39:03.689994 | 2021-05-14T18:24:37 | 2021-05-14T18:24:37 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,524 | r | straf.R | #' straf: STR Analysis for Forensics
#'
#' straf is a Shiny application to perform Short Tandem Repeats (STRs, also
#' known as microsatellites) data analysis. The application allows one to
#' compute forensic parameters, population genetics indices, and investigate
#' population structure through various methods an... |
f2d2b630dc143ee065560d504cf4493ce6de6407 | 1aff1c32b46fd0c88f97bbb787b49c46c4138c49 | /R/emodnet_wfs.R | ccd6c8caa8f9dce655bf4c9d56a6cf668692302f | [
"MIT"
] | permissive | EMODnet/EMODnetWFS | 31d6a48709cbee11a332b83fb23c31d7f788330a | 8b52b4de54ff9517da82932e6c46abc1ed0c48ba | refs/heads/main | 2023-05-22T12:47:09.644761 | 2023-04-13T07:03:42 | 2023-04-13T07:03:42 | 270,789,361 | 6 | 4 | NOASSERTION | 2023-04-11T12:22:36 | 2020-06-08T18:57:56 | R | UTF-8 | R | false | false | 335 | r | emodnet_wfs.R | .emodnet_wfs <- function() {
utils::read.csv(
system.file("services.csv", package = "EMODnetWFS"),
stringsAsFactors = FALSE
)
}
#' Available EMODnet Web Feature Services
#'
#' @return Tibble of available EMODnet Web Feature Services
#'
#' @examples
#' emodnet_wfs()
#' @export
emodnet_wfs <- memoise::memoise... |
172c49b51444b1b8c7297a04b9ee86406e0c3c4d | d79f3401546deaa155f0788139b5b5175be13091 | /plot4.R | 15b15ab25fd42f4b02db1ce34d4b526f3c198533 | [] | no_license | q5deng/ExData_Plotting1 | 760648888a038f3dc1eae1e3747c1575fa83730f | 718c530b6468c46e518d346ceaf079806aebbc16 | refs/heads/master | 2021-01-24T04:09:18.336813 | 2015-08-04T17:38:52 | 2015-08-04T17:38:52 | 40,198,493 | 0 | 0 | null | 2015-08-04T17:24:42 | 2015-08-04T17:24:41 | null | UTF-8 | R | false | false | 1,322 | r | plot4.R |
# plot4. R
## load data ##
dataset <- read.table("C:/Users/Deng/Documents/household_power_consumption.txt",
header = TRUE, sep = ";", na = "?",
colClasses = c("character", "character", rep("numeric",7)) )
attach(dataset)
## subset the data ##
newdat <- dataset[Date == "1/2/2007" | Date == "2/2/20... |
13fad7d669d94e4b477838d940e7b11eff622521 | c750c1991c8d0ed18b174dc72f3014fd35e5bd8c | /pkgs/oce/man/argoGrid.Rd | 4ef986099d66ad1aa65e829ba25d32154894875c | [] | no_license | vaguiar/EDAV_Project_2017 | 4b190e66fe7a6b4078cfe1b875bccd9b5a594b25 | 288ffaeec1cfdd873fe7439c0fa0c46a90a16a4f | refs/heads/base | 2021-01-23T02:39:36.272851 | 2017-05-01T23:21:03 | 2017-05-01T23:21:03 | 86,010,131 | 1 | 0 | null | 2017-05-01T23:43:04 | 2017-03-24T00:21:20 | HTML | UTF-8 | R | false | true | 2,649 | rd | argoGrid.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/argo.R
\name{argoGrid}
\alias{argoGrid}
\title{Grid Argo float data}
\usage{
argoGrid(argo, p, debug = getOption("oceDebug"), ...)
}
\arguments{
\item{argo}{A \code{argo} object to be gridded.}
\item{p}{Optional indication of the pressure le... |
30056500c64c92e31647af4018706ad769b0ab1b | 34f6961b79a5d283b50e6ba0792d8d9ddca796f4 | /R/normalize.R | b21921419239cf3637338c3561d03f34a56b8918 | [] | no_license | ttdtrang/cdev-paper | f9b364d9e1a7c82d4eecdb1740088174bb97f8b0 | 5020b44cc95cd5fba8ff69572a9cb48b36ca55b2 | refs/heads/main | 2023-06-24T19:17:00.967612 | 2021-07-22T21:59:16 | 2021-07-22T21:59:16 | 342,710,467 | 1 | 2 | null | null | null | null | UTF-8 | R | false | false | 5,596 | r | normalize.R |
#' normalize.by.qsmooth
#'
#' @import qsmooth
#' @export
normalize.by.qsmooth <- function(X, group_factor, ...) {
qs <- qsmooth::qsmooth(t(X), group_factor = group_factor, ...)
qs@qsmoothData %>%
t() %>%
return()
}
#' normalize.by.tmm
#'
#' Call calcNormFactors by edgeR
#' @import edgeR
#' @pa... |
d97871a968e2c4558820bcc5e0bb72123221f594 | 2a7e77565c33e6b5d92ce6702b4a5fd96f80d7d0 | /fuzzedpackages/Rmixmod/man/summary-methods.Rd | 8bb782132ef73ebb6c706a5b0aae6010a5cf953d | [] | no_license | akhikolla/testpackages | 62ccaeed866e2194652b65e7360987b3b20df7e7 | 01259c3543febc89955ea5b79f3a08d3afe57e95 | refs/heads/master | 2023-02-18T03:50:28.288006 | 2021-01-18T13:23:32 | 2021-01-18T13:23:32 | 329,981,898 | 7 | 1 | null | null | null | null | UTF-8 | R | false | true | 1,250 | rd | summary-methods.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/global.R, R/MultinomialParameter.R,
% R/GaussianParameter.R, R/CompositeParameter.R, R/MixmodResults.R,
% R/Mixmod.R, R/MixmodPredict.R
\docType{methods}
\name{summary}
\alias{summary}
\alias{summary,MultinomialParameter-method}
\alias{su... |
ec1a5fde40d31d65d7551c78ec39f15dd22b3e6e | fe43291e58d0ba74929b0c25e257072923c356d3 | /PCA_functions.R | 17d520a98b54477d9a557f569d7ee765680a186a | [] | no_license | Jing0831/Data-Mining-for-Business-Analytics | fad73dbb7d6218db64c0851af3012faebbfee055 | e05119576749a1a5cee75e27c6a0fc64b7693150 | refs/heads/main | 2023-07-31T22:30:58.199933 | 2021-09-21T23:48:14 | 2021-09-21T23:48:14 | 409,006,559 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 986 | r | PCA_functions.R | ## Five Element Analytics
## Author: Alex Pelaez
## Date Revised: 01-02-2019
##
## TO USE THIS
## Use the PCA function from FactomineR package and
## pass in the pca object into Pass in a vector
## Result will be the vector of min_max_normalization
#
# Example:
##
#Usage: communality(data)
#Example: p = PCA(house... |
bac466054ff4fa075f7253197e0198edfa817f27 | b39c8b303071e7aeaec8dd41a8bfffca3501b5f5 | /cachematrix.R | f0f0083d81d0b84a700484aa4ca897a7974bdbda | [] | no_license | PhilAIUK/ProgrammingAssignment2 | 3ef6da8fe5c9ed0979dd2a88adc142b614d72143 | ab5329caa9e5e3361d94a804df472d21951a9841 | refs/heads/master | 2020-04-21T19:22:48.181699 | 2019-02-08T23:13:35 | 2019-02-08T23:13:35 | 169,804,208 | 0 | 0 | null | 2019-02-08T21:56:49 | 2019-02-08T21:56:49 | null | UTF-8 | R | false | false | 1,565 | r | cachematrix.R | ## Put comments here that give an overall description of what your
## functions do
## These functions will show how we can retrieve data from the cache
## instead of re-calculating; which could be time consuming
## Write a short comment describing this function
## This function creates a "matrix" object and cache it... |
3a3b6bf6fc5296f931552b914a402bd0ac8375a1 | b287d87a513892632473e8348c2c017410fb5fd1 | /inst/doc/qtbase.R | 80aa5b57ef0fa7853bff267abbad6557564f1037 | [] | no_license | cran/qtbase | ec4194483b608ecb055ce4fd1b14693d0a311eb0 | d1e773fc79e5dae7148d1e52ef70be54795e9c95 | refs/heads/master | 2020-06-07T09:34:42.764850 | 2018-05-09T08:03:20 | 2018-05-09T08:03:20 | 17,698,852 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 8,223 | r | qtbase.R | ### R code from vignette source 'qtbase.Rnw'
###################################################
### code chunk number 1: setup
###################################################
options(width=72)
library(qtbase)
supported <-
!length(grep("darwin", R.version$platform)) ||
nzchar(Sys.getenv("SECURITYSESSIONID"))
#... |
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